import argparse
import matplotlib.pyplot as plt
import pandas_ta as ta
from pandas.plotting import register_matplotlib_converters
from gamestonk_terminal.helper_funcs import (
    check_positive,
    parse_known_args_and_warn,
    plot_autoscale,
)
from gamestonk_terminal.config_plot import PLOT_DPI
from gamestonk_terminal import feature_flags as gtff

register_matplotlib_converters()


def adx(l_args, s_ticker, s_interval, df_stock):
    parser = argparse.ArgumentParser(
        add_help=False,
        prog="adx",
        description="""
            The ADX is a Welles Wilder style moving average of the Directional Movement Index (DX).
            The values range from 0 to 100, but rarely get above 60. To interpret the ADX, consider
            a high number to be a strong trend, and a low number, a weak trend.
        """,
    )

    parser.add_argument(
        "-l",
        "--length",
        action="store",
        dest="n_length",
        type=check_positive,
        default=14,
        help="length",
    )
    parser.add_argument(
        "-s",
        "--scalar",
        action="store",
        dest="n_scalar",
        type=check_positive,
        default=100,
        help="scalar",
    )
    parser.add_argument(
        "-d",
        "--drift",
        action="store",
        dest="n_drift",
        type=check_positive,
        default=1,
        help="drift",
    )
    parser.add_argument(
        "-o",
        "--offset",
        action="store",
        dest="n_offset",
        type=check_positive,
        default=0,
        help="offset",
    )

    try:
        ns_parser = parse_known_args_and_warn(parser, l_args)
        if not ns_parser:
            return

        # Daily
        if s_interval == "1440min":
            df_ta = ta.adx(
                high=df_stock["2. high"],
                low=df_stock["3. low"],
                close=df_stock["5. adjusted close"],
                length=ns_parser.n_length,
                scalar=ns_parser.n_scalar,
                drift=ns_parser.n_drift,
                offset=ns_parser.n_offset,
            ).dropna()

        # Intraday
        else:
            df_ta = ta.adx(
                high=df_stock["2. high"],
                low=df_stock["3. low"],
                close=df_stock["4. close"],
                length=ns_parser.n_length,
                scalar=ns_parser.n_scalar,
                drift=ns_parser.n_drift,
                offset=ns_parser.n_offset,
            ).dropna()

        plot_adx(df_stock, s_ticker, df_ta)

        print("")

    except Exception as e:
        print(e)
        print("")


def plot_adx(df_stock, s_ticker, df_ta):
    plt.figure(figsize=plot_autoscale(), dpi=PLOT_DPI)
    plt.subplot(211)
    plt.plot(df_stock.index, df_stock["4. close"].values, "k", lw=2)
    plt.title(f"Average Directional Movement Index (ADX) on {s_ticker}")
    plt.xlim(df_stock.index[0], df_stock.index[-1])
    plt.ylabel("Share Price ($)")
    plt.grid(b=True, which="major", color="#666666", linestyle="-")
    plt.minorticks_on()
    plt.grid(b=True, which="minor", color="#999999", linestyle="-", alpha=0.2)
    plt.subplot(212)
    plt.plot(df_ta.index, df_ta.iloc[:, 0].values, "b", lw=2)
    plt.plot(df_ta.index, df_ta.iloc[:, 1].values, "g", lw=1)
    plt.plot(df_ta.index, df_ta.iloc[:, 2].values, "r", lw=1)
    plt.xlim(df_stock.index[0], df_stock.index[-1])
    plt.axhline(25, linewidth=3, color="k", ls="--")
    plt.legend(
        [
            f"ADX ({df_ta.columns[0]})",
            f"+DI ({df_ta.columns[1]})",
            f"- DI ({df_ta.columns[2]})",
        ]
    )
    plt.xlabel("Time")
    plt.grid(b=True, which="major", color="#666666", linestyle="-")
    plt.minorticks_on()
    plt.grid(b=True, which="minor", color="#999999", linestyle="-", alpha=0.2)
    plt.ylim([0, 100])

    if gtff.USE_ION:
        plt.ion()

    plt.show()


def aroon(l_args, s_ticker, s_interval, df_stock):
    parser = argparse.ArgumentParser(
        add_help=False,
        prog="aroon",
        description="""
            The word aroon is Sanskrit for "dawn's early light." The Aroon
            indicator attempts to show when a new trend is dawning. The indicator consists
            of two lines (Up and Down) that measure how long it has been since the highest
            high/lowest low has occurred within an n period range. \n \n When the Aroon Up is
            staying between 70 and 100 then it indicates an upward trend. When the Aroon Down
            is staying between 70 and 100 then it indicates an downward trend. A strong upward
            trend is indicated when the Aroon Up is above 70 while the Aroon Down is below 30.
            Likewise, a strong downward trend is indicated when the Aroon Down is above 70 while
            the Aroon Up is below 30. Also look for crossovers. When the Aroon Down crosses above
            the Aroon Up, it indicates a weakening of the upward trend (and vice versa).
        """,
    )

    parser.add_argument(
        "-l",
        "--length",
        action="store",
        dest="n_length",
        type=check_positive,
        default=25,
        help="length",
    )
    parser.add_argument(
        "-s",
        "--scalar",
        action="store",
        dest="n_scalar",
        type=check_positive,
        default=100,
        help="scalar",
    )
    parser.add_argument(
        "-o",
        "--offset",
        action="store",
        dest="n_offset",
        type=check_positive,
        default=0,
        help="offset",
    )

    try:
        ns_parser = parse_known_args_and_warn(parser, l_args)
        if not ns_parser:
            return

        df_ta = ta.aroon(
            high=df_stock["2. high"],
            low=df_stock["3. low"],
            length=ns_parser.n_length,
            scalar=ns_parser.n_scalar,
            offset=ns_parser.n_offset,
        ).dropna()

        plt.figure(figsize=plot_autoscale(), dpi=PLOT_DPI)
        plt.subplot(311)
        # Daily
        if s_interval == "1440min":
            plt.plot(df_stock.index, df_stock["5. adjusted close"].values, "k", lw=2)
        # Intraday
        else:
            plt.plot(df_stock.index, df_stock["4. close"].values, "k", lw=2)

        plt.title(f"Aroon on {s_ticker}")
        plt.xlim(df_stock.index[0], df_stock.index[-1])
        plt.ylabel("Share Price ($)")
        plt.grid(b=True, which="major", color="#666666", linestyle="-")
        plt.minorticks_on()
        plt.grid(b=True, which="minor", color="#999999", linestyle="-", alpha=0.2)

        plt.subplot(312)
        plt.plot(df_ta.index, df_ta.iloc[:, 0].values, "r", lw=2)
        plt.plot(df_ta.index, df_ta.iloc[:, 1].values, "g", lw=2)
        plt.xlim(df_stock.index[0], df_stock.index[-1])
        plt.axhline(50, linewidth=1, color="k", ls="--")
        plt.legend(
            [f"Aroon DOWN ({df_ta.columns[0]})", f"Aroon UP ({df_ta.columns[1]})"]
        )
        plt.grid(b=True, which="major", color="#666666", linestyle="-")
        plt.minorticks_on()
        plt.grid(b=True, which="minor", color="#999999", linestyle="-", alpha=0.2)
        plt.ylim([0, 100])

        plt.subplot(313)
        plt.plot(df_ta.index, df_ta.iloc[:, 2].values, "b", lw=2)
        plt.xlabel("Time")
        plt.legend([f"Aroon OSC ({df_ta.columns[2]})"])
        plt.grid(b=True, which="major", color="#666666", linestyle="-")
        plt.minorticks_on()
        plt.grid(b=True, which="minor", color="#999999", linestyle="-", alpha=0.2)
        plt.ylim([-100, 100])

        if gtff.USE_ION:
            plt.ion()

        plt.show()
        print("")

    except Exception as e:
        print(e)
        print("")
